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Zhe Xu

Zhe Xu appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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hep-phnucl-thastro-ph.SReess.SYSystems and ControlComputer VisionArtificial Intelligenceeess.IVhep-thMachine LearningFormal Languages and Automata TheoryLogic in Computer Sciencemath.OCMultiagent Systemsnucl-exphysics.med-phRoboticshep-exmath.LOphysics.acc-phphysics.comp-phphysics.opticsphysics.space-ph

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Published work

80 published item(s)

preprint2026arXiv

HCInfer: An Efficient Inference System via Error Compensation for Resource-Constrained Devices

LLMs often struggle with memory-constrained deployment on consumer-grade hardware due to their massive parameter sizes. While existing solutions such as model compression and offloading improve deployment feasibility, they often suffer from substantial accuracy degradation or severe throughput bottlenecks. Recent error compensation methods recover accuracy through auxiliary LoRA-style branches, and we observe that these branches are inherently amenable to offloading: they require substantial parameter storage but access only a small subset of compensation parameters during each inference step. Motivated by this opportunity, we propose HCInfer, a heterogeneous inference system that offloads residual compensation to the CPU while executing the compressed backbone on the GPU, and further introduces an asynchronous compensation pipeline and sensitivity-aware dynamic rank allocation to hide compensation overhead and maximize accuracy recovery. Experimental results show that HCInfer achieves a maximum accuracy improvement of 5.2% on downstream tasks compared to compression model and sustaining a maximum speedup of 10.4x compared to full-precision model.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Inferring Causal Graph Temporal Logic Formulas to Expedite Reinforcement Learning in Temporally Extended Tasks

Decision-making tasks often unfold on graphs with spatial-temporal dynamics. Black-box reinforcement learning often overlooks how local changes spread through network structure, limiting sample efficiency and interpretability. We present GTL-CIRL, a closed-loop framework that simultaneously learns policies and mines Causal Graph Temporal Logic (Causal GTL) specifications. The method shapes rewards with robustness, collects counterexamples when effects fail, and uses Gaussian Process (GP) driven Bayesian optimization to refine parameterized cause templates. The GP models capture spatial and temporal correlations in the system dynamics, enabling efficient exploration of complex parameter spaces. Case studies in gene and power networks show faster learning and clearer, verifiable behavior compared to standard RL baselines.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

Simultaneous observations of a breakout current sheet and a flare current sheet in a coronal jet event

Previous studies have revealed that solar coronal jets triggered by the eruption of mini-filaments (MFs) conform to the famous magnetic-breakout mechanism. In such scenario, a breakout current sheet (BCS) and a flare current sheet (FCS) should be observed during the jets. With high spatial and temporal resolution data from the SDO, the NVST, the RHESSI, the Wind, and the GOES, we present observational evidence of a BCS and a FCS formation during coronal jets driven by a MF eruption occurring in the active region NOAA 11726 on 2013 April 21. Magnetic field extrapolation show that the MF was enclosed by a fan-spine magnetic structure. The MF was activated by flux cancellation under it, and then slowly rose. A BCS formed when the magnetic fields wrapping the MF squeezed to antidirectional external open fields. Simultaneously, one thin bright jet and two bidirectional jet-like structures were observed. As the MF erupted as a blowout jet, a FCS was formed when the two distended legs inside the MF field came together. One end of the FCS connected the post-flare loops. The peak temperature of BCS was calculated to be 2.5 MK. The length, width and peak temperature of FCS was calculated to be 4.35-4.93 Mm, 1.31-1.45 Mm, and 2.5 MK, respectively. The magnetic reconnection rate associated with the FCS was estimated to be from 0.266 to 0.333. This event also related to a type III radio burst, indicating its influence on interplanetary space. These observations support the scenario of the breakout model as the trigger mechanism of coronal jets, and flux cancellation was the driver of this event.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

The Decay of Two Adjacent Sunspots Associated with Moving Magnetic Features

The relationship between the decay of sunspots and moving magnetic features (MMFs) plays an important role in understanding the evolution of active regions. We present observations of two adjacent sunspots, the gap between them, and a lot of MMFs propagating from the gap and the sunspots' outer edges in NOAA Active Region 13023. The MMFs are divided into two types based on their magnetic field inclination angle: vertical (0°<γ<45°) and horizontal (45°<γ<90°) MMFs (V-MMFs and H-MMFs, respectively). The main results are as follows: (1) the mean magnetic flux decay rates of the two sunspots are -1.7*10^20 and -1.4*10^20 Mx/day; (2) the magnetic flux generation rate of all MMFs is calculated to be -1.9 *10^21 Mx/day, which is on average 5.6 times higher than the total magnetic flux loss rate of the sunspots; (3) the magnetic flux of V-MMFs (including a pore separated from the sunspots) is 1.4 times larger than the total lost magnetic flux of the two sunspots, and in a later stage when the pore has passed through the reference ellipse, the magnetic flux generation rate of the V-MMFs is almost the same as the magnetic flux loss rate of the sunspots; and (4) within the gap, the magnetic flux of V-MMFs is one third of the total magnetic flux. Few V-MMFs stream out from the sunspots at the nongap region. All observations suggest that MMFs with vertical magnetic fields are closely related to the disintegration of the sunspot, and most of the MMFs from the gap may originate directly from the sunspot umbra.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Constrained Active Classification Using Partially Observable Markov Decision Processes

In this work, we study the problem of actively classifying the attributes of dynamical systems characterized as a finite set of Markov decision process (MDP) models. We are interested in finding strategies that actively interact with the dynamical system and observe its reactions so that the attribute of interest is classified efficiently with high confidence. We present a decision-theoretic framework based on partially observable Markov decision processes (POMDPs). The proposed framework relies on assigning a classification belief (a probability distribution) to the attributes of interest. Given an initial belief, a confidence level over which a classification decision can be made, a cost bound, safe belief sets, and a finite time horizon, we compute POMDP strategies leading to classification decisions. We present three different algorithms to compute such strategies. The first algorithm computes the optimal strategy exactly by value iteration. To overcome the computational complexity of computing the exact solutions, we propose a second algorithm based on adaptive sampling and a third based on a Monte Carlo tree search to approximate the optimal probability of reaching a classification decision. We illustrate the proposed methodology using examples from medical diagnosis, security surveillance, and wildlife classification.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Onset mechanism of an inverted U-shaped solar filament eruption revealed by NVST, SDO, and STEREO-A observations

Utilizing observations from the New Vacuum Solar Telescope (NVST), Solar Dynamics Observatory (SDO), and Solar Terrestrial Relations Observatory-Ahead (STEREO-A), we investigate the event from two distinct observational perspectives: on the solar disk using NVST and SDO, and on the solar limb using STEREO-A. We employ both a non-linear force-free field model and a potential field model to reconstruct the coronal magnetic field, aiming to understand its magnetic properties. Two precursor jet-like activities were observed before the eruption, displaying an untwisted rotation. The second activity released an estimated twist of over two turns. During these two jet-like activities, Y-shaped brightenings, newly emerging magnetic flux accompanied by magnetic cancellation, and the formation of newly moving fibrils were identified. Combining these observational features, it can be inferred that these two precursor jet-like activities released the magnetic field constraining the filament and were triggered by newly emerging magnetic flux. Before the filament eruption, it was observed that some moving flows had been ejected from the site as the onset of two jet-like activities, indicating the same physical process as two jet-like activities. Extrapolations revealed that the filament laid under the height of the decay index of 1.0 and had strong magnetic field (540 Gauss) and a high twisted number (2.4 turns) before the eruption. An apparent rotational motion was observed during the filament eruption. We deduce that the solar filament, exhibiting an inverted U-shape, is a significantly twisted flux rope. The eruption of the filament was initiated by the release of constraining magnetic fields through continuous magnetic reconnection. This reconnection process was triggered by the emergence of newly magnetic flux.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Propagation of spin channel waves

A mutilated model is constructed to approximate the collision term of spin Boltzmann equation that incorporates newly appearing collisional invariants i.e, the total angular momentum. With recourse to degenerate perturbation theory, the dispersion relations of hydrodynamic modes are formulated, among which spin modes are responsible for spin equilibration. We find that the non-locality does not change the sound speed but slows down the propagation of spin channel waves. The damping rates of spin modes are close to those of spinless modes over a reasonable parameter value range. The results reveal that both spin and momentum should be treated simultaneously in a unified transport framework. In the nonrelativistic limit, the short-wavelength behavior for normal modes is also explored and there exists a critical point for every distinct discrete mode over which only quasiparticle modes contribute.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A partial filament eruption in three steps induced by external magnetic reconnection

We present an investigation of partial filament eruption on 2012 June 17 in the active region NOAA 11504. For the first time, we observed the vertical splitting process during the partial eruption with high resolution narrow band images at 10830 . The active filament was rooted in a small sunspot of the active region. Particularly, it underwent the partial eruption in three steps, i.e. the precursor, the first eruption, and the second eruption, while the later two were associated with a C1.0 flare and a C3.9 flare, respectively. During the precursor, slow magnetic reconnection took place between the filament and the adjoining loops that also rooted in the sunspot. The continuous reconnection not only caused the filament to split into three groups of threads vertically but also formed a new filament, which was growing and accompanied brightening took place around the site. Subsequently, the growing filament erupted together with one group splitted threads, resulted in the first eruption. At the beginning of the first eruption, a subsequent magnetic reconnection occurred between the erupting splitted threads and another ambient magnetic loop. After about three minutes, the second eruption occurred as a result of the eruption of two larger unstable filaments induced by the magnetic reconnection. The high-resolution observation provides a direct evidence that magnetic reconnection between filament and its ambient magnetic fields could induce the vertical splitting of the filament, resulting in partial eruption.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation

Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially, the consistency-based approaches have attracted more attention for their superior performance, wherein the real labels are only utilized to supervise their paired images via supervised loss while the unlabeled images are exploited by enforcing the perturbation-based \textit{"unsupervised"} consistency without explicit guidance from those real labels. However, intuitively, the expert-examined real labels contain more reliable supervision signals. Observing this, we ask an unexplored but interesting question: can we exploit the unlabeled data via explicit real label supervision for semi-supervised training? To this end, we discard the previous perturbation-based consistency but absorb the essence of non-parametric prototype learning. Based on the prototypical network, we then propose a novel cyclic prototype consistency learning (CPCL) framework, which is constructed by a labeled-to-unlabeled (L2U) prototypical forward process and an unlabeled-to-labeled (U2L) backward process. Such two processes synergistically enhance the segmentation network by encouraging more discriminative and compact features. In this way, our framework turns previous \textit{"unsupervised"} consistency into new \textit{"supervised"} consistency, obtaining the \textit{"all-around real label supervision"} property of our method. Extensive experiments on brain tumor segmentation from MRI and kidney segmentation from CT images show that our CPCL can effectively exploit the unlabeled data and outperform other state-of-the-art semi-supervised medical image segmentation methods.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Bio-inspired Intelligence with Applications to Robotics: A Survey

In the past decades, considerable attention has been paid to bio-inspired intelligence and its applications to robotics. This paper provides a comprehensive survey of bio-inspired intelligence, with a focus on neurodynamics approaches, to various robotic applications, particularly to path planning and control of autonomous robotic systems. Firstly, the bio-inspired shunting model and its variants (additive model and gated dipole model) are introduced, and their main characteristics are given in detail. Then, two main neurodynamics applications to real-time path planning and control of various robotic systems are reviewed. A bio-inspired neural network framework, in which neurons are characterized by the neurodynamics models, is discussed for mobile robots, cleaning robots, and underwater robots. The bio-inspired neural network has been widely used in real-time collision-free navigation and cooperation without any learning procedures, global cost functions, and prior knowledge of the dynamic environment. In addition, bio-inspired backstepping controllers for various robotic systems, which are able to eliminate the speed jump when a large initial tracking error occurs, are further discussed. Finally, the current challenges and future research directions are discussed in this paper.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Consensus Formation Tracking for Multiple AUV Systems Using Distributed Bioinspired Sliding Mode Control

Consensus formation tracking of multiple autonomous underwater vehicles (AUVs) subject to nonlinear and uncertain dynamics is a challenging problem in robotics. To tackle this challenge, a distributed bioinspired sliding mode controller is proposed in this paper. First, the conventional sliding mode controller (SMC) is presented, and the consensus problem is addressed on the basis of graph theory. Next, to tackle the high frequency chattering issue in SMC scheme and meanwhile improve the robustness to the noises, a bioinspired approach is introduced, in which a neural dynamic model is employed to replace the nonlinear sign or saturation function in the synthesis of conventional sliding mode controllers. Furthermore, the input-to-state stability of the resulting closed-loop system is proved in the presence of bounded lumped disturbance by the Lyapunov stability theory. Finally, simulation experiments are conducted to demonstrate the effectiveness of the proposed distributed formation control protocol.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Deformer: Towards Displacement Field Learning for Unsupervised Medical Image Registration

Recently, deep-learning-based approaches have been widely studied for deformable image registration task. However, most efforts directly map the composite image representation to spatial transformation through the convolutional neural network, ignoring its limited ability to capture spatial correspondence. On the other hand, Transformer can better characterize the spatial relationship with attention mechanism, its long-range dependency may be harmful to the registration task, where voxels with too large distances are unlikely to be corresponding pairs. In this study, we propose a novel Deformer module along with a multi-scale framework for the deformable image registration task. The Deformer module is designed to facilitate the mapping from image representation to spatial transformation by formulating the displacement vector prediction as the weighted summation of several bases. With the multi-scale framework to predict the displacement fields in a coarse-to-fine manner, superior performance can be achieved compared with traditional and learning-based approaches. Comprehensive experiments on two public datasets are conducted to demonstrate the effectiveness of the proposed Deformer module as well as the multi-scale framework.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Double-Uncertainty Guided Spatial and Temporal Consistency Regularization Weighting for Learning-based Abdominal Registration

In order to tackle the difficulty associated with the ill-posed nature of the image registration problem, regularization is often used to constrain the solution space. For most learning-based registration approaches, the regularization usually has a fixed weight and only constrains the spatial transformation. Such convention has two limitations: (i) Besides the laborious grid search for the optimal fixed weight, the regularization strength of a specific image pair should be associated with the content of the images, thus the "one value fits all" training scheme is not ideal; (ii) Only spatially regularizing the transformation may neglect some informative clues related to the ill-posedness. In this study, we propose a mean-teacher based registration framework, which incorporates an additional temporal consistency regularization term by encouraging the teacher model's prediction to be consistent with that of the student model. More importantly, instead of searching for a fixed weight, the teacher enables automatically adjusting the weights of the spatial regularization and the temporal consistency regularization by taking advantage of the transformation uncertainty and appearance uncertainty. Extensive experiments on the challenging abdominal CT-MRI registration show that our training strategy can promisingly advance the original learning-based method in terms of efficient hyperparameter tuning and a better tradeoff between accuracy and smoothness.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Incomplete electromagnetic response of hot QCD matter

The electromagnetic response of hot QCD matter to decaying external magnetic fields is investigated. We examine the validity of Ohm's law and find that the induced electric current increases from zero and relaxes towards the value from Ohm's law. The relaxation time is larger than the lifetime of the external magnetic field for the QCD matter in relativistic heavy-ion collisions. The lower than expected electric current significantly suppresses the induced magnetic field and makes the electromagnetic response incomplete. We demonstrate the incomplete electromagnetic response of hot QCD matter by calculations employing the parton transport model combined with the solution of Maxwell's equations. Our results show a strong suppression by two orders of magnitude in the magnetic field, relatively to calculations assuming the validity of Ohm's law. This may undermine experimental efforts to measure magnetic-field-related effects in heavy-ion collisions.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Joint Inference of Reward Machines and Policies for Reinforcement Learning

Incorporating high-level knowledge is an effective way to expedite reinforcement learning (RL), especially for complex tasks with sparse rewards. We investigate an RL problem where the high-level knowledge is in the form of reward machines, i.e., a type of Mealy machine that encodes the reward functions. We focus on a setting in which this knowledge is a priori not available to the learning agent. We develop an iterative algorithm that performs joint inference of reward machines and policies for RL (more specifically, q-learning). In each iteration, the algorithm maintains a hypothesis reward machine and a sample of RL episodes. It derives q-functions from the current hypothesis reward machine, and performs RL to update the q-functions. While performing RL, the algorithm updates the sample by adding RL episodes along which the obtained rewards are inconsistent with the rewards based on the current hypothesis reward machine. In the next iteration, the algorithm infers a new hypothesis reward machine from the updated sample. Based on an equivalence relationship we defined between states of reward machines, we transfer the q-functions between the hypothesis reward machines in consecutive iterations. We prove that the proposed algorithm converges almost surely to an optimal policy in the limit if a minimal reward machine can be inferred and the maximal length of each RL episode is sufficiently long. The experiments show that learning high-level knowledge in the form of reward machines can lead to fast convergence to optimal policies in RL, while standard RL methods such as q-learning and hierarchical RL methods fail to converge to optimal policies after a substantial number of training steps in many tasks.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Magnetic field induced hair structure in charmonium gluon-dissociation

We study electromagnetic field effect on charmonium gluon-dissociation in quark-gluon plasma. With the effective Hamiltonian derived from QCD multipole expansion under an external electromagnetic field, we first solve the two-body Schrödinger equation for a pair of charm quarks with mean field potentials for color and electromagnetic interactions and obtain the charmonium binding energies and wave functions, and then calculate the gluon-dissociation cross-section and decay width by taking the color electric and magnetic dipole interactions as perturbations above the mean field and employing Fermi's Golden Rule. Considering the charmonium deformation in magnetic field, the discrete Landau energy levels make the dissociation cross-section grow hair, and the electric dipole channel is significantly changed, especially for the $P-$wave states $χ_{c0}$ and $χ_{c\pm}$. From our numerical calculation, the magnetic field strength $eB=5~m_π^2$ already changes the gluon dissociation strongly, which may indicate measurable effects in high-energy nuclear collisions.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Non-Parametric Neuro-Adaptive Coordination of Multi-Agent Systems

We develop a learning-based algorithm for the distributed formation control of networked multi-agent systems governed by unknown, nonlinear dynamics. Most existing algorithms either assume certain parametric forms for the unknown dynamic terms or resort to unnecessarily large control inputs in order to provide theoretical guarantees. The proposed algorithm avoids these drawbacks by integrating neural network-based learning with adaptive control in a two-step procedure. In the first step of the algorithm, each agent learns a controller, represented as a neural network, using training data that correspond to a collection of formation tasks and agent parameters. These parameters and tasks are derived by varying the nominal agent parameters and the formation specifications of the task in hand, respectively. In the second step of the algorithm, each agent incorporates the trained neural network into an online and adaptive control policy in such a way that the behavior of the multi-agent closed-loop system satisfies a user-defined formation task. Both the learning phase and the adaptive control policy are distributed, in the sense that each agent computes its own actions using only local information from its neighboring agents. The proposed algorithm does not use any a priori information on the agents' unknown dynamic terms or any approximation schemes. We provide formal theoretical guarantees on the achievement of the formation task.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Non-Parametric Neuro-Adaptive Formation Control

We develop a learning-based algorithm for the distributed formation control of networked multi-agent systems governed by unknown, nonlinear dynamics. Most existing algorithms either assume certain parametric forms for the unknown dynamic terms or resort to unnecessarily large control inputs in order to provide theoretical guarantees. The proposed algorithm avoids these drawbacks by integrating neural network-based learning with adaptive control in a two-step procedure. In the first step of the algorithm, each agent learns a controller, represented as a neural network, using training data that correspond to a collection of formation tasks and agent parameters. These parameters and tasks are derived by varying the nominal agent parameters and a user-defined formation task to be achieved, respectively. In the second step of the algorithm, each agent incorporates the trained neural network into an online and adaptive control policy in such a way that the behavior of the multi-agent closed-loop system satisfies the user-defined formation task. Both the learning phase and the adaptive control policy are distributed, in the sense that each agent computes its own actions using only local information from its neighboring agents. The proposed algorithm does not use any a priori information on the agents' unknown dynamic terms or any approximation schemes. We provide formal theoretical guarantees on the achievement of the formation task.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Reconfiguration and eruption of a solar filament by magnetic reconnection with an emerging magnetic field

Both observations and simulations suggest that the solar filament eruption is closely related to magnetic flux emergence. It is thought that the eruption is triggered by magnetic reconnection between the filament and the emerging flux. However, the details of such a reconnection are rarely presented. In this study, we report the detailed reconnection between a filament and its nearby emerging fields, that led to the reconfiguration and subsequent partial eruption of the filament located over the polarity inversion line of active region 12816. Before the reconnection, we observed repeated brightenings in the filament at a location that overlies a site of magnetic flux cancellation. Plasmoids form at this brightening region, and propagate bi-directionally along the filament. These indicate the tether-cutting reconnection that results in the formation and eruption of a flux rope. To the northwest of the filament, magnetic fields emerge, and reconnect with the context ones, resulting in repeated jets. Afterwards, another magnetic fields emerge near the northwestern filament endpoints, and reconnect with the filament, forming the newly reconnected filament and loops. Current sheet repeatedly occurs at the interface, with the mean temperature and emission measure of 1.7 MK and 1.1$\times$10$^{28}$ cm$^{-5}$. Plasmoids form in the current sheet, and propagate along it and further along the newly reconnected filament and loops. The newly reconnected filament then erupts, while the unreconnected filament remains stable. We propose that besides the orientation of emerging fields, some other parameters, such as the position, distance, strength, and area, are also crucial for triggering the filament eruption.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction

Recently, deep neural networks have greatly advanced undersampled Magnetic Resonance Image (MRI) reconstruction, wherein most studies follow the one-anatomy-one-network fashion, i.e., each expert network is trained and evaluated for a specific anatomy. Apart from inefficiency in training multiple independent models, such convention ignores the shared de-aliasing knowledge across various anatomies which can benefit each other. To explore the shared knowledge, one naive way is to combine all the data from various anatomies to train an all-round network. Unfortunately, despite the existence of the shared de-aliasing knowledge, we reveal that the exclusive knowledge across different anatomies can deteriorate specific reconstruction targets, yielding overall performance degradation. Observing this, in this study, we present a novel deep MRI reconstruction framework with both anatomy-shared and anatomy-specific parameterized learners, aiming to "seek common ground while reserving differences" across different anatomies.Particularly, the primary anatomy-shared learners are exposed to different anatomies to model flourishing shared knowledge, while the efficient anatomy-specific learners are trained with their target anatomy for exclusive knowledge. Four different implementations of anatomy-specific learners are presented and explored on the top of our framework in two MRI reconstruction networks. Comprehensive experiments on brain, knee and cardiac MRI datasets demonstrate that three of these learners are able to enhance reconstruction performance via multiple anatomy collaborative learning.

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preprint2022arXiv

Statistical analysis of circular-ribbon flares

Circular-ribbon flares (CFs) are a special type of solar flares owing to their particular magnetic topology. In this paper, we conducted a comprehensive statistical analysis of 134 CFs from 2011 September to 2017 June, including four B-class, 82 C-class, 40 M-class, and eight X-class flares, respectively. The flares were observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) spacecraft. The physical properties of CFs are derived, including the location, area ($A_{CF}$), equivalent radius ($r_{CF}$) assuming a semi-spherical fan dome, lifetime ($τ_{CF}$), and peak SXR flux in 1$-$8 Å. It is found that all CFs are located in active regions, with the latitudes between -30$^\circ$ and 30$^\circ$. The distributions of areas and lifetimes could be fitted with a log-normal function. There is a positive correlation between the lifetime and area. The peak SXR flux in 1$-$8 Å is well in accord with a power-law distribution with an index of $-$1.42. For the 134 CFs, 57\% of them are accompanied by remote brightenings or ribbons. A positive correlation exists between the total length ($L_{RB}$) and average distance ($D_{RB}$) of remote brightenings. About 47\% and 51\% of the 134 CFs are related to type III radio bursts and jets, respectively. The association rates are independent of flare energies. About 38\% of CFs are related to mini-filament eruptions, and the association rates increase with flare classes. Only 28\% of CFs are related to CMEs, meaning that a majority of them are confined rather than eruptive events. There is a positive correlation between the CME speed and peak SXR flux in 1$-$8 Å, and faster CMEs tend to be wider.

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preprint2022arXiv

Sunspot shearing and sudden retraction motion associated with the 2013 August 17 M3.3 Flare

In this Letter, we give a detailed analysis to the M3.3 class flare that occurred on August 17, 2013 (SOL2013-08-17T18:16). It presents a clear picture of mutual magnetic interaction initially from the photosphere to the corona via the abrupt rapid shearing motion of a small sunspot before the flare, and then suddenly from the corona back to the photosphere via the sudden retraction motion of the same sunspot during the flare impulsive phase. About 10 hours before the flare, a small sunspot in the active region NOAA 11818 started to move northeast along a magnetic polarity inversion line (PIL), creating a shearing motion that changed the quasi-static state of the active region. A filament right above the PIL was activated following the movement of the sunspot and then got partially erupted. The eruption eventually led to the M3.3 flare. The sunspot was then suddenly pulled back to the opposite direction upon the flare onset. During the backward motion, the Lorentz force underwent a simultaneous impulsive change both in magnitude and direction. Its directional change is found to be conformable with the retraction motion. The observation provides direct evidence for the role of the shearing motion of the sunspot in powering and triggering the flare. It especially confirms that the abrupt motion of a sunspot during a solar flare is the result of a back reaction caused by the reconfiguration of the coronal magnetic field.

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preprint2022arXiv

Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification

Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the significant data imbalance and obvious extraneous artifacts, i.e., the hair and ruler markings, discriminative feature extraction from dermoscopic images is very challenging. In this study, we seek to resolve these problems respectively towards better representation learning for lesion features. Specifically, a GAN-based data augmentation (GDA) strategy is adapted to generate synthetic melanoma-positive images, in conjunction with the proposed implicit hair denoising (IHD) strategy. Wherein the hair-related representations are implicitly disentangled via an auxiliary classifier network and reversely sent to the melanoma-feature extraction backbone for better melanoma-specific representation learning. Furthermore, to train the IHD module, the hair noises are additionally labeled on the ISIC2020 dataset, making it the first large-scale dermoscopic dataset with annotation of hair-like artifacts. Extensive experiments demonstrate the superiority of the proposed framework as well as the effectiveness of each component. The improved dataset publicly avaliable at https://github.com/kirtsy/DermoscopicDataset.

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preprint2022arXiv

Trust It or Not: Confidence-Guided Automatic Radiology Report Generation

Medical imaging plays a pivotal role in diagnosis and treatment in clinical practice. Inspired by the significant progress in automatic image captioning, various deep learning (DL)-based methods have been proposed to generate radiology reports for medical images. Despite promising results, previous works overlook the uncertainties of their models and are thus unable to provide clinicians with the reliability/confidence of the generated radiology reports to assist their decision-making. In this paper, we propose a novel method to explicitly quantify both the visual uncertainty and the textual uncertainty for DL-based radiology report generation. Such multi-modal uncertainties can sufficiently capture the model confidence degree at both the report level and the sentence level, and thus they are further leveraged to weight the losses for more comprehensive model optimization. Experimental results have demonstrated that the proposed method for model uncertainty characterization and estimation can produce more reliable confidence scores for radiology report generation, and the modified loss function, which takes into account the uncertainties, leads to better model performance on two public radiology report datasets. In addition, the quality of the automatically generated reports was manually evaluated by human raters and the results also indicate that the proposed uncertainties can reflect the variance of clinical diagnosis.

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preprint2022arXiv

Weighted Graph-Based Signal Temporal Logic Inference Using Neural Networks

Extracting spatial-temporal knowledge from data is useful in many applications. It is important that the obtained knowledge is human-interpretable and amenable to formal analysis. In this paper, we propose a method that trains neural networks to learn spatial-temporal properties in the form of weighted graph-based signal temporal logic (wGSTL) formulas. For learning wGSTL formulas, we introduce a flexible wGSTL formula structure in which the user's preference can be applied in the inferred wGSTL formulas. In the proposed framework, each neuron of the neural networks corresponds to a subformula in a flexible wGSTL formula structure. We initially train a neural network to learn the wGSTL operators and then train a second neural network to learn the parameters in a flexible wGSTL formula structure. We use a COVID-19 dataset and a rain prediction dataset to evaluate the performance of the proposed framework and algorithms. We compare the performance of the proposed framework with three baseline classification methods including K-nearest neighbors, decision trees, support vector machine, and artificial neural networks. The classification accuracy obtained by the proposed framework is comparable with the baseline classification methods.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Magneto-acoustic oscillations observed in a solar plage region

We gave an extensive study for the quasi-periodic perturbations on the time profiles of the line of sight (LOS) magnetic field in 10x10 sub-areas in a solar plage region (corresponds to a facula on the photosphere). The perturbations are found to be associated with enhancement of He I 10830 A absorption in a moss region, which is connected to loops with million-degree plasma. FFT analysis to the perturbations gives a kind of spectrum similar to that of Doppler velocity: a number of discrete periods around 5 minutes. The amplitudes of the magnetic perturbations are found to be proportional to magnetic field strength over these sub-areas. In addition, magnetic perturbations lag behind a quarter of cycle in phase with respect to the p-mode Doppler velocity. We show that the relationships can be well explained with an MHD solution for the magneto-acoustic oscillations in high-\b{eta} plasma. Observational analysis also shows that, for the two regions with the stronger and weaker magnetic field, the perturbations are always anti-phased. All findings show that the magnetic perturbations are actually magneto-acoustic oscillations on the solar surface, the photosphere, powered by p-mode oscillations. The findings may provide a new diagnostic tool for exploring the relationship between magneto-acoustic oscillations and the heating of solar upper atmosphere, as well as their role in helioseismology.

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preprint2021arXiv

Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking

In this paper, we develop safe reinforcement-learning-based controllers for systems tasked with accomplishing complex missions that can be expressed as linear temporal logic specifications, similar to those required by search-and-rescue missions. We decompose the original mission into a sequence of tracking sub-problems under safety constraints. We impose the safety conditions by utilizing barrier functions to map the constrained optimal tracking problem in the physical space to an unconstrained one in the transformed space. Furthermore, we develop policies that intermittently update the control signal to solve the tracking sub-problems with reduced burden in the communication and computation resources. Subsequently, an actor-critic algorithm is utilized to solve the underlying Hamilton-Jacobi-Bellman equations. Finally, we support our proposed framework with stability proofs and showcase its efficacy via simulation results.

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preprint2020arXiv

Adaptive Teaching of Temporal Logic Formulas to Learners with Preferences

Machine teaching is an algorithmic framework for teaching a target hypothesis via a sequence of examples or demonstrations. We investigate machine teaching for temporal logic formulas -- a novel and expressive hypothesis class amenable to time-related task specifications. In the context of teaching temporal logic formulas, an exhaustive search even for a myopic solution takes exponential time (with respect to the time span of the task). We propose an efficient approach for teaching parametric linear temporal logic formulas. Concretely, we derive a necessary condition for the minimal time length of a demonstration to eliminate a set of hypotheses. Utilizing this condition, we propose a myopic teaching algorithm by solving a sequence of integer programming problems. We further show that, under two notions of teaching complexity, the proposed algorithm has near-optimal performance. The results strictly generalize the previous results on teaching preference-based version space learners. We evaluate our algorithm extensively under a variety of learner types (i.e., learners with different preference models) and interactive protocols (e.g., batched and adaptive). The results show that the proposed algorithms can efficiently teach a given target temporal logic formula under various settings, and that there are significant gains of teaching efficacy when the teacher adapts to the learner's current hypotheses or uses oracles.

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preprint2020arXiv

Adversarial Uni- and Multi-modal Stream Networks for Multimodal Image Registration

Deformable image registration between Computed Tomography (CT) images and Magnetic Resonance (MR) imaging is essential for many image-guided therapies. In this paper, we propose a novel translation-based unsupervised deformable image registration method. Distinct from other translation-based methods that attempt to convert the multimodal problem (e.g., CT-to-MR) into a unimodal problem (e.g., MR-to-MR) via image-to-image translation, our method leverages the deformation fields estimated from both: (i) the translated MR image and (ii) the original CT image in a dual-stream fashion, and automatically learns how to fuse them to achieve better registration performance. The multimodal registration network can be effectively trained by computationally efficient similarity metrics without any ground-truth deformation. Our method has been evaluated on two clinical datasets and demonstrates promising results compared to state-of-the-art traditional and learning-based methods.

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preprint2020arXiv

Do Public Datasets Assure Unbiased Comparisons for Registration Evaluation?

With the increasing availability of new image registration approaches, an unbiased evaluation is becoming more needed so that clinicians can choose the most suitable approaches for their applications. Current evaluations typically use landmarks in manually annotated datasets. As a result, the quality of annotations is crucial for unbiased comparisons. Even though most data providers claim to have quality control over their datasets, an objective third-party screening can be reassuring for intended users. In this study, we use the variogram to screen the manually annotated landmarks in two datasets used to benchmark registration in image-guided neurosurgeries. The variogram provides an intuitive 2D representation of the spatial characteristics of annotated landmarks. Using variograms, we identified potentially problematic cases and had them examined by experienced radiologists. We found that (1) a small number of annotations may have fiducial localization errors; (2) the landmark distribution for some cases is not ideal to offer fair comparisons. If unresolved, both findings could incur bias in registration evaluation.

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preprint2020arXiv

Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers

We present a novel network pruning algorithm called Dynamic Sparse Training that can jointly find the optimal network parameters and sparse network structure in a unified optimization process with trainable pruning thresholds. These thresholds can have fine-grained layer-wise adjustments dynamically via backpropagation. We demonstrate that our dynamic sparse training algorithm can easily train very sparse neural network models with little performance loss using the same number of training epochs as dense models. Dynamic Sparse Training achieves the state of the art performance compared with other sparse training algorithms on various network architectures. Additionally, we have several surprising observations that provide strong evidence for the effectiveness and efficiency of our algorithm. These observations reveal the underlying problems of traditional three-stage pruning algorithms and present the potential guidance provided by our algorithm to the design of more compact network architectures.

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preprint2020arXiv

Policy Synthesis for Factored MDPs with Graph Temporal Logic Specifications

We study the synthesis of policies for multi-agent systems to implement spatial-temporal tasks. We formalize the problem as a factored Markov decision process subject to so-called graph temporal logic specifications. The transition function and the spatial-temporal task of each agent depend on the agent itself and its neighboring agents. The structure in the model and the specifications enable to develop a distributed algorithm that, given a factored Markov decision process and a graph temporal logic formula, decomposes the synthesis problem into a set of smaller synthesis problems, one for each agent. We prove that the algorithm runs in time linear in the total number of agents. The size of the synthesis problem for each agent is exponential only in the number of neighboring agents, which is typically much smaller than the number of agents. We demonstrate the algorithm in case studies on disease control and urban security. The numerical examples show that the algorithm can scale to hundreds of agents.

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preprint2020arXiv

Policy Synthesis for Switched Linear Systems with Markov Decision Process Switching

We study the synthesis of mode switching protocols for a class of discrete-time switched linear systems in which the mode jumps are governed by Markov decision processes (MDPs). We call such systems MDP-JLS for brevity. Each state of the MDP corresponds to a mode in the switched system. The probabilistic state transitions in the MDP represent the mode transitions. We focus on finding a policy that selects the switching actions at each mode such that the switched system that follows these actions is guaranteed to be stable. Given a policy in the MDP, the considered MDP-JLS reduces to a Markov jump linear system (MJLS). {We consider both mean-square stability and stability with probability one. For mean-square stability, we leverage existing stability conditions for MJLSs and propose efficient semidefinite programming formulations to find a stabilizing policy in the MDP. For stability with probability one, we derive new sufficient conditions and compute a stabilizing policy using linear programming. We also extend the policy synthesis results to MDP-JLS with uncertain mode transition probabilities.

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preprint2020arXiv

Robust Inference and Verification of Temporal Logic Classifier-in-the-loop Systems

Autonomous systems embedded with machine learning modules often rely on deep neural networks for classifying different objects of interest in the environment or different actions or strategies to take for the system. Due to the non-linearity and high-dimensionality of deep neural networks, the interpretability of the autonomous systems is compromised. Besides, the machine learning methods in autonomous systems are mostly data-intensive and lack commonsense knowledge and reasoning that are natural to humans. In this paper, we propose the framework of temporal logic classifier-in-the-loop systems. The temporal logic classifiers can output different actions to take for an autonomous system based on the environment, such that the behavior of the autonomous system can satisfy a given temporal logic specification. Our approach is robust and provably-correct, as we can prove that the behavior of the autonomous system can satisfy a given temporal logic specification in the presence of (bounded) disturbances.

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preprint2020arXiv

Temporal Logic Inference for Hybrid System Observation with Spatial and Temporal Uncertainties

In this paper, we present a mechanism for building hybrid system observers to differentiate between specific positions of the hybrid system. The mechanism is designed through inferring metric temporal logic (MTL) formulae from simulated trajectories from the hybrid system. We first approximate the system behavior by simulating finitely many trajectories with timerobust tube segments around them. These time-robust tube segments account for both spatial and temporal uncertainties that exist in the hybrid system with initial state variations. The inferred MTL formulae classify different time-robust tube segments and thus can be used for classifying the hybrid system behaviors in a provably correct fashion. We implement our approach on a model of a smart building testbed to distinguish two cases of room occupancy.

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preprint2019arXiv

Calculation of anisotropic transport coefficients for an ultrarelativistic Boltzmann gas in a magnetic field within a kinetic approach

According to the Kubo formulas we employ the (3+1)-d parton cascade, Boltzmann approach of multiparton scatterings (BAMPS), to calculate the anisotropic transport coefficients (shear viscosity and electric conductivity) for an ultrarelativistic Boltzmann gas in the presence of a magnetic field. The results are compared with those recently obtained by using the Grad's approximation. We find good agreements between both results, which confirms the general use of the derived Kubo formulas for calculating the anisotropic transport coefficients of quark-gluon plasma in a magnetic field.

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preprint2019arXiv

Recurrent Two-Sided Loop Jets Caused by Magnetic Reconnection between Erupting Minifilaments and Nearby Large Filament

Using high spatial and temporal data from the New Vacuum Solar Telescope (NVST) and the Solar Dynamics Observatory (SDO), we present unambiguous observations of recurrent two-sided loop jets caused by magnetic reconnection between erupting minifilaments and nearby large filament. The observations demonstrate that three two-sided loop jets, which ejected along the large filament in opposite directions, had similar appearance and originated from the same region. We find that a minifilament erupted and drove the first jet. It reformed at the same neutral line later, and then underwent partial and total eruptions, drove the second and third jets, respectively. In the course of the jets, cool plasma was injected into the large filament. Furthermore, persistent magnetic flux cancelation occurred at the neutral line under the minifilament before its eruption and continued until the end of the observation. We infer that magnetic flux cancellation may account for building and then triggering the minifilament to erupt to produce the two-sided loop jets. This observation not only indicates that two-sided loop jets can be driven by minifilament eruptions, but also sheds new light on our understanding of the recurrent mechanism of two-sided loop jets.

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preprint2016arXiv

Census Signal Temporal Logic Inference for Multi-Agent Group Behavior Analysis

In this paper, we define a novel census signal temporal logic (CensusSTL) that focuses on the number of agents in different subsets of a group that complete a certain task specified by the signal temporal logic (STL). CensusSTL consists of an "inner logic" STL formula and an "outer logic" STL formula. We present a new inference algorithm to infer CensusSTL formulae from the trajectory data of a group of agents. We first identify the "inner logic" STL formula and then infer the subgroups based on whether the agents' behaviors satisfy the "inner logic" formula at each time point. We use two different approaches to infer the subgroups based on similarity and complementarity, respectively. The "outer logic" CensusSTL formula is inferred from the census trajectories of different subgroups. We apply the algorithm in analyzing data from a soccer match by inferring the CensusSTL formula for different subgroups of a soccer team.

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preprint2015arXiv

Glueballs amass at RHIC and LHC Colliders! - The early quarkless 1st order phase transition at $T=270$ MeV - from pure Yang-Mills glue plasma to GlueBall-Hagedorn states

The early stage of high multiplicity pp, pA and AA collider is represented by a nearly quarkless, hot, deconfined pure gluon plasma. According to pure Yang-Mills Lattice Gauge Theory, this hot pure glue matter undergoes, at a high temperature, $T_c = 270$ MeV, a first order phase transition into a confined Hagedorn-GlueBall fluid. These new scenario should be characterized by a suppression of high $p_T$ photons and dileptons, baryon suppression and enhanced strange meson production. We propose to observe this newly predicted class of events at LHC and RHIC.

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preprint2015arXiv

Influence of multiple in-medium scattering processes on the momentum imbalance of reconstructed di-jets

Experimental data measured in sqrt(s)=2.76 TeV Pb+Pb collisions at the LHC show a significant enhancement of events with an unbalanced pair of reconstructed jet momenta in comparison with p+p collisions. This enhancement of momentum imbalance is supposed to be caused by the different momentum loss of the initial back-to-back di-partons by scatterings within the created dense medium. For investigating the underlying partonic momentum loss we employ the on-shell transport model BAMPS (Boltzmann Approach for Multi-Parton Scattering) for full heavy-ion collisions, which numerically solves the 3+1D Boltzmann equation based on 2->2 as well as inelastic 2<->3 scattering processes, together with PYTHIA initial state conditions for the parton showers. Due to the employed test-particle approach jet reconstruction within BAMPS events is not trivial. We introduce a method that nevertheless allows the microscopic simulation of the full evolution of the shower particles, recoiled medium particles, and the underlying bulk medium in one common microscopic framework. With this method it is possible to investigate the role of the medium recoil for the momentum imbalance A_J while using well-established background subtraction algorithms. Due to the available particle information in configuration as well as momentum space within BAMPS, it is additionally possible to reproduce the entire evolution of the reconstructed jets within the medium. With this information we investigate the sensitivity of the jet momentum loss from the difference in the partonic in-medium path lengths.

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preprint2015arXiv

Magnetic Field Effect on Charmonium Production in High Energy Nuclear Collisions

It is important to understand the strong external magnetic field generated at the very beginning of high energy nuclear collisions. We study the effect of the magnetic field on the charmonium yield and anisotropic distribution in Pb+Pb collisions at the LHC energy. The time dependent Schrödinger equation is employed to describe the motion of $c\bar{c}$ pairs. We compare our model prediction of non- collective anisotropic parameter $v_2$ of $J/ψ$s with CMS data at high transverse momentum. This is the first attempt to measure the magnetic field in high energy nuclear collisions.

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preprint2015arXiv

Robust scatter correction method for cone-beam CT using an interlacing-slit plate

Cone-beam computed tomography (CBCT) has been widely used in medical imaging and industrial nondestructive testing, but the presence of scattered radiation will cause significant reduction of image quality. In this article, a robust scatter correction method for CBCT using an interlacing-slit plate (ISP) is carried out for convenient practice. Firstly, a Gaussian filtering method is proposed to compensate the missing data of the inner scatter image, and simultaneously avoid too-large values of calculated inner scatter and smooth the inner scatter field. Secondly, an interlacing-slit scan without detector gain correction is carried out to enhance the practicality and convenience of the scatter correction method. Finally, a denoising step for scatter-corrected projection images is added in the process flow to control the noise amplification. The experimental results show that the improved method can not only make the scatter correction more robust and convenient, but also achieve a good quality of scatter-corrected slice images.

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preprint2015arXiv

Thermalization of gluons with Bose-Einstein condensation

We study the thermalization of gluons far from thermal equilibrium in relativistic kinetic theory. The initial distribution of gluons is assumed to resemble that in the early stage of ultrarelativistic heavy ion collisions. Only elastic scatterings in static, nonexpanding gluonic matter are considered. At first we show that the occurrence of condensation in the limit of vanishing particle mass requires a general constraint for the scattering matrix element. Then the thermalization of gluons with Bose-Einstein condensation is demonstrated in a transport calculation. We see a continuously increasing overpopulation of low energy gluons, followed by a decrease to the equilibrium distribution, when the condensation occurs. The times of the completion of the gluon condensation and of the entropy production are calculated. These times scale inversely with the energy density.

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preprint2014arXiv

Elastic and radiative heavy quark interactions in ultra-relativistic heavy-ion collisions

Elastic and radiative heavy quark interactions with light partons are studied with the partonic transport description BAMPS (Boltzmann Approach to MultiParton Scatterings). After calculating the cross section of radiative processes for finite masses in the improved Gunion-Bertsch approximation and verifying this calculation by comparing to the exact result, we study elastic and radiative heavy quark energy loss in a static medium of quarks and gluons. Furthermore, the full 3+1D space-time evolution of gluons, light quarks, and heavy quarks in ultra-relativistic heavy-ion collisions at the BNL Relativistic Heavy-Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC) are calculated with BAMPS including elastic and radiative heavy flavor interactions. Treating light and heavy particles on the same footing in the same framework, we find that the experimentally measured nuclear modification factor of charged hadrons and D mesons at the LHC can be simultaneously described. In addition, we calculate the heavy flavor evolution with an improved screening procedure from hard-thermal-loop calculations and confront the results with experimental data of the nuclear modification factor and the elliptic flow of heavy flavor particles at RHIC and LHC.

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preprint2014arXiv

Electric conductivity of the quark-gluon plasma investigated using a perturbative QCD based parton cascade

Electric conductivity is sensitive to effective cross sections among the particles of the partonic medium. We investigate the electric conductivity of a hot plasma of quarks and gluons, solving the relativistic Boltzmann equation. In order to extract this transport coefficient, we employ the Green-Kubo formalism and, independently, a method motivated by the classical definition of electric conductivity. To this end we evaluate the static electric diffusion current upon the influence of an electric field. Both methods give identical results. For the first time, we obtain numerically the Drude electric conductivity formula for an ultrarelativistic gas of quarks and gluons employing constant isotropic binary cross sections. Furthermore, we extract the electric conductivity for a system of massless quarks and gluons including screened binary and inelastic, radiative $2\leftrightarrow 3$ perturbative QCD scattering. Comparing with recent lattice results, we find an agreement in the temperature dependence of the conductivity.

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preprint2014arXiv

Elliptic flow and nuclear modification factor in ultra-relativistic heavy-ion collisions within a partonic transport model

The quark gluon plasma produced in ultra-relativistic heavy-ion collisions exhibits remarkable features. It behaves like a nearly perfect liquid with a small shear viscosity to entropy density ratio and leads to the quenching of highly energetic particles. We show that both effects can be understood for the first time within one common framework. Employing the parton cascade Boltzmann Approach to Multi-Parton Scatterings (BAMPS), the microscopic interactions and the space-time evolution of the quark gluon plasma are calculated by solving the relativistic Boltzmann equation. Based on cross sections obtained from perturbative QCD with explicitly taking the running coupling into account, we calculate the nuclear modification factor and elliptic flow in ultra-relativistic heavy-ion collisions. With only one single parameter associated with coherence effects of medium-induced gluon radiation, the experimental data of both observables can be understood on a microscopic level. Furthermore, we show that perturbative QCD interactions with a running coupling lead to a sufficiently small shear viscosity to entropy density ratio of the quark gluon plasma, which provides a microscopic explanation for the observations stated by hydrodynamic calculations.

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preprint2014arXiv

Medium Effects on Charmonium Production at ultrarelativistic energies available at the CERN Large Haron Collider

We investigate with a transport approach the cold and hot nuclear matter effects on the charmonium transverse momentum distributions in relativistic heavy ion collisions. The newly defined nuclear modification factor $r_{AA}=\langle p_{T}^2\rangle_{AA}/\langle p_{T}^2\rangle_{pp}$ and elliptic flow $v_2$ for $J/ψ$ are sensitive to the nature of the hot medium and the thermalization of heavy quarks. From SPS through RHIC to LHC colliding energies, we observe dramatic changes in the centrality dependence of $r_{AA}$. We find that at LHC energy, the finally observed charmonia are dominated by the regeneration from thermalized heavy quarks.

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preprint2014arXiv

Momentum imbalance of D mesons in ultra-relativistic heavy-ion collisions at LHC

As a new observable for heavy flavor correlations the momentum imbalance $A_D$ of D mesons is proposed. It is defined analogously to the jet momentum imbalance $A_J$ of fully reconstructed jets. However, since D mesons are flavor tagged particles, no jet reconstruction is necessary. $A_D$ quantifies the influence of the medium created in heavy-ion collisions on correlated charm pairs. We present results with the partonic transport model Boltzmann Approach to MultiParton Scatterings (BAMPS), which describes well the nuclear modification factor and elliptic flow of all heavy flavor particles at RHIC and LHC. The $A_D$ distribution in heavy-ion collisions at LHC is shifted to larger values of $A_D$ compared to proton-proton collisions. We argue that this shift is due to medium effects and can be explained partially by a path length imbalance of charm pairs and partially by momentum fluctuations in the initial charm pair distribution.

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preprint2014arXiv

Point spread function modeling and images restoration for cone-beam CT

X-ray cone-beam computed tomography (CT) has the notable features such as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection images degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed firstly. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection images restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection images restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods.

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preprint2014arXiv

Shear viscosity of an ultrarelativistic Boltzmann gas with isotropic inelastic scattering processes

We derive an analytic expression for the shear viscosity of an ultra-relativistic gas in presence of both elastic $2\to 2$ and inelastic $2\leftrightarrow 3$ processes with isotropic differential cross sections. The derivation is based on the entropy principle and Grad's approximation for the off-equilibrium distribution function. The obtained formula relates the shear viscosity coefficient $η$ to the total cross sections $σ_{22}$ and $σ_{23}$ of the elastic resp. inelastic processes. The values of shear viscosity extracted using the Green-Kubo formula from kinetic transport calculations are shown to be in excellent agreement with the analytic results which demonstrates the validity of the derived formula.

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preprint2013arXiv

Heavy vs. light flavor energy loss within a partonic transport model

The full space-time evolution of gluons, light and heavy quarks in ultra-relativistic heavy-ion collisions is studied within the partonic transport model Boltzmann Approach to MultiParton Scatterings (BAMPS). We discuss for light and heavy quarks the elastic and radiative energy loss with a running coupling. Radiative processes, in particular, are implemented through an improved version of the Gunion-Bertsch matrix element, which is derived from comparisons to the exact result, explicitly taking finite heavy quark masses into account. Subsequently, we present results with and without radiative processes and compare them to experimental data at LHC. A focus is put on the nuclear modification factor of charged hadrons and D mesons.

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preprint2013arXiv

Radiative parton processes in perturbative QCD - an improved version of the Gunion and Bertsch cross section from comparisons to the exact result

In this work we compare the Gunion-Bertsch approximation of the leading order perturbative QCD radiation matrix element to the exact result. To this end, we revisit the derivation of the Gunion-Bertsch approximation as well as perform extensive numerical comparisons of the Gunion-Bertsch and the exact result. We find that when employing the matrix elements to obtain rates or cross sections from phase space integration, the amplitude by Gunion and Bertsch deviates from the correct result in characteristic regions of the phase space. We propose an improved version of the Gunion-Bertsch matrix element which agrees very well with the exact result in all phase space regions.

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preprint2012arXiv

Dissipative hydrodynamics for multi-component systems

Second-order dissipative hydrodynamic equations for each component of a multi-component system are derived using the entropy principle. Comparison of the solutions with kinetic transport results demonstrates validity of the obtained equations. We demonstrate how the shear viscosity of the total system can be calculated in terms of the involved cross sections and partial densities. Presence of the inter-species interactions leads to a characteristic time-dependence of the shear viscosity of the mixture, which also means that the shear viscosity of a mixture cannot be calculated using the Green-Kubo formalism the way it has been done recently. This finding is of interest for understanding of the shear viscosity of a quark-gluon-plasme extracted from comparisons of hydrodynamic simulations with experimental results from RHIC and LHC.

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preprint2012arXiv

Open heavy flavor and J/psi at RHIC and LHC

The suppression and collective flow of open and hidden heavy flavor in ultra-relativistic heavy ion collisions is studied with the partonic transport model Boltzmann Approach to MultiParton Scatterings (BAMPS). Charm and bottom quarks interact with the rest of the medium via elastic scatterings with an improved Debye screening and a running coupling. Heavy flavor electron data from RHIC can only be described if the cross section is multiplied with K=3.5 to mimic the contribution from radiative processes. With the same value for K we compare to elliptic flow data of D mesons at the LHC and find a good agreement. However, the nuclear modification factor of D mesons, non-prompt J/psi, muons, and electrons at the LHC is underestimated in our calculations. In addition, we present first BAMPS results on the suppression and elliptic flow of J/psi mesons, which are treated in the same framework.

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preprint2012arXiv

Open heavy flavor in Pb+Pb collisions at sqrt(s)=2.76 TeV within a transport model

The space-time evolution of open heavy flavor is studied in Pb+Pb collisions at sqrt(s)=2.76 TeV using the partonic transport model Boltzmann Approach to MultiParton Scatterings (BAMPS). An updated version of BAMPS is presented which allows interactions among all partons: gluons, light quarks, and heavy quarks. Heavy quarks, in particular, interact with the rest of the medium via binary scatterings with a running coupling and a Debye screening which is matched by comparing to hard thermal loop calculations. The lack of radiative processes in the heavy flavor sector is accounted for by scaling the binary cross section with a phenomenological factor K=3.5, which describes well the elliptic flow v_2 and nuclear modification factor R_AA at RHIC. Within this framework we calculate in a comprehensive study the v_2 and R_AA of all interesting open heavy flavor particles at the LHC: electrons, muons, D mesons, and non-prompt J/psi from B mesons. We compare to experimental data, where it is already available, or make predictions. To do this accurately next-to-leading order initial heavy quark distributions are employed which agree well with proton-proton data of heavy flavor at sqrt(s)=7 TeV.

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preprint2012arXiv

RHIC and LHC phenomena with an unified parton transport

We discuss recent applications of the partonic pQCD based cascade model BAMPS with focus on heavy-ion phenomeneology in hard and soft momentum range. The nuclear modification factor as well as elliptic flow are calculated in BAMPS for RHIC end LHC energies. These observables are also discussed within the same framework for charm and bottom quarks. Contributing to the recent jet-quenching investigations we present first preliminary results on application of jet reconstruction algorithms in BAMPS. Finally, collective effects induced by jets are investigated: we demonstrate the development of Mach cones in ideal matter as well in the highly viscous regime.

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preprint2012arXiv

Transition from ideal to viscous Mach cones in BAMPS

We investigate in a microscopical transport model the evolution of conical structures originating from the supersonic projectile moving through the matter of ultrarelativistic particles. Using different scenarios for the interaction between projectile and matter, and different transport properties of the matter, we study the formation and structure of Mach cones. Furthermore, the two-particle correlations for different viscosities are extracted from the numerical calculations and we compare them to an analytical approximation. In addition, by adjusting he cross section we investigate the influence of the viscosity to the structure of Mach cones.

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preprint2011arXiv

Dissipative hydrodynamics for relativistic multi-component systems

Second-order dissipative hydrodynamic equations for each component of a multi-component system are derived using the entropy principle. The shear viscosity of the whole system, appearing in the equation summed-up over all components, is related to the partial shear pressures and cannot be considered as an external parameter. We demonstrate that it is essential to solve hydrodynamic equations for each component, instead of treating a mixture as an effective one-component system with a free parameter $η/s$. Thus, extractions of the $η/s$ value of the QGP at RHIC and LHC have to be reexamined.

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preprint2011arXiv

Elliptic and Triangular Flow and their Correlation in Ultrarelativistic High Multiplicity Proton Proton Collisions at 14 TeV

The spatial configuration of initial partons in high-multiplicity proton-proton scatterings at 14 TeV is assumed as three randomly positioned "hot spots". The parton momentum distribution in the hot spots is calculated by HIJING2.0 with some modifications. This initial condition causes not only large eccentricity $ε_2$ but also triangularity $ε_3$ and the correlation of $ε_2-ε_3$ event-plane angles. The final elliptic flow $v_2$, triangular flow $v_3$, and the correlation of $v_2-v_3$ event-plane angles are calculated by using the parton cascade model BAMPS to simulate the space-time parton evolution. Our results show that the $v_2-v_3$ correlation is different from that of $ε_2-ε_3$. This finding indicates that translations of different Fourier components of the initial spatial asymmetry to the final flow components are not independent. A dynamical correlation between the elliptic and triangular flow appears during the collective expansion.

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preprint2011arXiv

Elliptic flow and energy loss of heavy quarks in ultra-relativistic heavy ion collisions

The space-time propagation of heavy quarks in ultra-relativistic heavy ion collisions is studied within the partonic transport model Boltzmann Approach of MultiParton Scatterings (BAMPS). In this model heavy quarks interact with the partonic medium via binary scatterings. The cross sections for these interactions are calculated with leading order perturbative QCD, but feature a more precise Debye screening derived within the hard thermal loop approximation and obey the running of the coupling. Within this framework the elliptic flow and the nuclear modification factor of heavy quarks are computed for RHIC and LHC energies and compared to available experimental data. It is found that binary scatterings alone cannot reproduce the data and, therefore, radiative corrections have to be taken into account.

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preprint2011arXiv

Extraction of shear viscosity in stationary states of relativistic particle systems

Starting from a classical picture of shear viscosity we construct a stationary velocity gradient in a microscopic parton cascade. Employing the Navier-Stokes ansatz we extract the shear viscosity coefficient $η$. For elastic isotropic scatterings we find an excellent agreement with the analytic values. This confirms the applicability of this method. Furthermore for both elastic and inelastic scatterings with pQCD based cross sections we extract the shear viscosity coefficient $η$ for a pure gluonic system and find a good agreement with already published calculations.

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preprint2011arXiv

Heavy quarks and charmonium at RHIC and LHC within a partonic transport model

Heavy quark and charmonium production as well as their space-time evolution are studied in transport simulations of heavy-ion collisions at RHIC and LHC. In the partonic transport model Boltzmann Approach of MultiParton Scatterings (BAMPS) heavy quarks can be produced in initial hard parton scatterings or during the evolution of the quark-gluon plasma. Subsequently, they interact with the medium via binary scatterings with a running coupling and a more precise Debye screening which is derived from hard thermal loop calculations, participate in the flow and lose energy. We present results of the elliptic flow and nuclear modification factor of heavy quarks and compare them to available data. Furthermore, preliminary results on J/psi suppression at forward and mid-rapidity are reported for central and non-central collisions at RHIC. For this, we study cold nuclear matter effects and the dissociation as well as regeneration of J/psi in the quark-gluon plasma.

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preprint2011arXiv

Jet quenching and elliptic flow at RHIC and LHC within a pQCD-based partonic transport model

Fully dynamic simulations of heavy ion collisions at RHIC and at LHC energies within the perturbative QCD-based partonic transport model BAMPS (Boltzmann Approach to Multi-Parton Scatterings) are presented, focusing on the simultaneous investigation of jet quenching and elliptic flow. The model features inelastic 2 <-> 3 processes based on the Gunion-Bertsch matrix element and has recently been extended to include light quark degrees of freedom, allowing for direct comparison to hadronic data on the nuclear modification factor via a fragmentation scheme for high-pT partons. The nuclear modification factor of neutral pions in central Au+Au collisions at RHIC energy is compared to experimental data. Furthermore first results on the nuclear modification factor and the integrated elliptic flow of charged hadrons in Pb+Pb collisions at LHC are presented and compared to recent ALICE data. These investigations are complemented by a study on the suppression of D-mesons at LHC based on elastic interactions with the medium.

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preprint2011arXiv

Open heavy flavor at RHIC and LHC in a partonic transport model

Heavy quarks are a unique probe to study the medium produced in ultra-relativistic heavy ion collisions. Within the partonic transport model Boltzmann approach to multi-parton scatterings (BAMPS) the production, energy loss and elliptic flow of heavy quarks are investigated in 3+1 dimensional simulations of the quark gluon plasma evolution. With only binary interactions between heavy quarks and particles from the medium calculated within perturbative QCD, the results on elliptic flow and the nuclear modification factor are not compatible with experimental data from RHIC and LHC. However, if the binary cross section is multiplied with K=4 both the elliptic flow and the nuclear modification factor are simultaneously described at RHIC and also LHC. Furthermore, preliminary results are presented that the implementation of radiative processes leads to a stronger suppression which agrees well with the measured nuclear modification factor at RHIC without the need of any K factor.

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preprint2010arXiv

A relativistic dissipative hydrodynamic description for systems including particle number changing processes

Relativistic dissipative hydrodynamic equations are extended by taking into account particle number changing processes in a gluon system, which expands in one dimension boost-invariantly. Chemical equilibration is treated by a rate equation for the particle number density based on Boltzmann equation and Grad's ansatz for the off-equilibrium particle phase space distribution. We find that not only the particle production, but also the temperature and the momentum spectra of the gluon system, obtained from the hydrodynamic calculations, are sensitive to the rates of particle number changing processes. Comparisons of the hydrodynamic calculations with the transport ones employing the parton cascade BAMPS show the inaccuracy of the rate equation at large shear viscosity to entropy density ratio. To improve the rate equation, the Grad's ansatz has to be modified beyond the second moments in momentum.

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preprint2010arXiv

Bulk matter evolution and extraction of jet transport parameter in heavy-ion collisions at RHIC

Within the picture of jet quenching induced by multiple parton scattering and gluon bremsstrahlung, medium modification of parton fragmentation functions and therefore the suppression of large transverse momentum hadron spectra are controlled by both the value and the space-time profile of the jet transport parameter along the jet propagation path. Experimental data on single hadron suppression in high-energy heavy-ion collisions at the RHIC energy are analyzed within the higher-twist (HT) approach to the medium modified fragmentation functions and the next-to-leading order (NLO) perturbative QCD (pQCD) parton model. Assuming that the jet transport parameter $\hat q$ is proportional to the particle number density in both QGP and hadronic phase, experimental data on jet quenching in deeply inelastic scattering (DIS) off nuclear targets can provide guidance on $\hat q_{h}$ in the hot hadronic matter. One can then study the dependence of extracted initial value of jet quenching parameter $\hat q_{0}$ at initial time $τ_{0}$ on the bulk medium evolution. Effects of transverse expansion, radial flow, phase transition and non-equilibrium evolution are examined. The extracted values are found to vary from $\hat q_{0}τ_{0}= 0.54$ GeV$^{2}$ in the (1+3)d ideal hydrodynamic model to 0.96 GeV$^{2}$ in a cascade model, with the main differences coming from the initial non-equilibrium evolution and the later hadronic evolution. The overall contribution to jet quenching from the hadronic phase, about 22-44%, is found to be significant. Therefore, realistic description of the early non-equilibrium parton evolution and later hadronic interaction will be critical for accurate extraction of the jet transport parameter in the strongly interacting QGP phase in high-energy heavy-ion collisions.

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preprint2010arXiv

Dependence of elliptic flow on number of parton degrees of freedom

We calculate the elliptic flow parameter $v_2$ for Au+Au collisions at $\sqrt{s_{NN}}=200$ GeV employing the parton cascade BAMPS (Boltzmann Approach of Multiparton Scatterings). Besides gluon interactions including the bremsstrahlung process, interactions with quarks are considered in an effective, but approximate way to investigate the dependence of the collective flow on the number of parton degrees of freedom. We find that $v_2$ as a function of the transverse momentum $p_T$ is sensitive to the number of parton degrees of freedom, whereas the $p_T$ averaged $v_2$ does not. When including quarks, $v_2(p_T)$ shifts to lower $p_T$, the parton transverse momentum spectra become softer and the mean parton transverse momenta decrease.

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preprint2010arXiv

Energy loss in a partonic transport model including bremsstrahlung processes

A detailed investigation of the energy loss of gluons that traverse a thermal gluonic medium simulated within the perturbative QCD--based transport model BAMPS (a Boltzmann approach to multiparton scatterings) is presented in the first part of this work. For simplicity the medium response is neglected in these calculations. The energy loss from purely elastic interactions is compared to the case where radiative processes are consistently included based on the matrix element by Gunion and Bertsch. From this comparison gluon multiplication processes gg -> ggg are found to be the dominant source of energy loss within the approach employed here. The consequences for the quenching of gluons with high transverse momentum in fully dynamic simulations of Au+Au collisions at the RHIC energy of sqrt(s) = 200 AGeV are discussed in the second major part of this work. The results for central collisions as discussed in a previous publication are revisited and first results on the nuclear modification factor R_AA for non-central Au+Au collisions are presented. They show a decreased quenching compared to central collisions while retaining the same shape. The investigation of the elliptic flow v2 is extended up to non-thermal transverse momenta of 10 GeV, exhibiting a maximum v2 at roughly 4 to 5 GeV and a subsequent decrease. Finally the sensitivity of the aforementioned results on the specific implementation of the effective modeling of the Landau-Pomeranchuk-Migdal (LPM) effect via a formation time based cut-off is explored.

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preprint2010arXiv

Heavy quark production at RHIC and LHC within a partonic transport model

The production and space-time evolution of charm and bottom quarks in nucleus-nucleus collisions at RHIC and LHC are investigated with the partonic transport model BAMPS (Boltzmann Approach of MultiParton Scatterings). Heavy quarks, produced in primary hard parton scatterings during nucleon-nucleon collisions, are sampled using the Monte Carlo event generator PYTHIA or the leading order mini-jet model in conjunction with the Glauber model, revealing a strong sensitivity on the parton distribution functions, scales, and heavy quark mass. In a comprehensive study exploring different charm masses, K factors, and possible initial gluon conditions, secondary production and the evolution of heavy quarks are examined within a fully dynamic BAMPS simulation for central heavy ion collisions at RHIC and LHC. Although charm production in the quark-gluon plasma can be neglected at RHIC, it is significant at LHC but very sensitive to the initial conditions and the charm mass. Bottom production in the quark-gluon plasma, however, is negligible both at RHIC and LHC.

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preprint2010arXiv

Heavy quarks at RHIC and LHC within a partonic transport model

Production and space-time evolution of heavy quarks in central and non-central heavy-ion collisions at RHIC and LHC are studied with the partonic transport model Boltzmann Approach of MultiParton Scatterings (BAMPS). In addition to the initially created heavy quarks in hard parton scatterings during nucleon-nucleon collisions, secondary heavy quark production in the quark-gluon plasma is investigated and the sensitivity on various parameters is estimated. In BAMPS heavy quarks scatter with particles of the medium via elastic collisions, whose cross section is calculated with the running coupling and a more precise implementation of Debye screening. In this framework, we compute the elliptic flow and nuclear modification factor of heavy quarks and compare it to the experimental data.

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preprint2010arXiv

Investigation of jet quenching and elliptic flow within a pQCD-based partonic transport model

The partonic transport model BAMPS (a Boltzmann approach to multiparton scatterings) is employed to investigate different aspects of heavy ion collisions within a common framework based on perturbative QCD. This report focuses on the joint investigation of the collective behavior of the created medium and the energy loss of high-pT gluons traversing this medium. To this end the elliptic flow and the nuclear modification factor of gluons in heavy ion collisions at 200 AGeV are simulated with BAMPS. The mechanism for the energy loss of high energy gluons within BAMPS is studied in detail. For this, purely elastic interactions are compared to radiative processes, gg -> ggg, that are implemented based on the matrix element by Gunion and Bertsch. The latter are found to be the dominant source of energy loss within the framework employed in this work.

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preprint2010arXiv

Jets and flow within a pQCD-based partonic transport model

We present fully dynamic simulations of heavy ion collisions at RHIC energies within the perturbative QCD-based partonic transport model BAMPS, focusing on the simultaneous investigation of jet-quenching and elliptic flow. The model consistently features elastic and inelastic 2 -> 3 processes, the latter being based on the Gunion-Bertsch matrix element. We discuss first attempts to extend the model to include light quark degrees of freedom and study the energy loss of high energy gluons and quarks in a static partonic medium. The difference between gluons and quarks in inelastic processes is found to be weaker than expected from color factors, due to a self-quenching effect associated with a cut-off modeling the LPM effect.

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preprint2010arXiv

Production and elliptic flow of heavy quarks at RHIC and LHC within a partonic transport model

Production and elliptic flow of heavy quarks are investigated in nucleus-nucleus collisions at RHIC and LHC within the Boltzmann Approach of MultiParton Scatterings (BAMPS). The initial heavy quark yield is estimated with the leading order mini-jet model and compared to PYTHIA for several parton distribution functions. Secondary production of heavy quarks in the quark-gluon plasma is examined within the full 3+1 dimensional BAMPS simulation of heavy ion collisions. At RHIC this yield is negligible, but for LHC charm production in the QGP plays a significant role. In addition, we study the elliptic flow of charm quarks at RHIC with the result that leading order processes are not sufficient to describe the experimental data.

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preprint2010arXiv

Production, elliptic flow and energy loss of heavy quarks in the quark-gluon plasma

Production, elliptic flow and the nuclear modification factor of charm and bottom quarks are studied in central and non-central heavy-ion collisions at RHIC and LHC using the partonic transport model Boltzmann Approach of MultiParton Scatterings (BAMPS). Employing an initial heavy quark yield obtained with PYTHIA the full space-time evolution of charm and bottom quarks in the quark-gluon plasma (QGP) is carried out with BAMPS, taking also secondary production in the QGP into account. Only elastic collisions of heavy quarks with particles from the medium cannot describe the experimentally observed elliptic flow and nuclear modification factor. However, using an improved Debye screening and the running coupling yields a result which is much closer to data.

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preprint2010arXiv

Relativistic Shock Waves and Mach Cones in Viscous Gluon Matter

To investigate the formation and the propagation of relativistic shock waves in viscous gluon matter we solve the relativistic Riemann problem using a microscopic parton cascade. We demonstrate the transition from ideal to viscous shock waves by varying the shear viscosity to entropy density ratio $η/s$. Furthermore we compare our results with those obtained by solving the relativistic causal dissipative fluid equations of Israel and Stewart (IS), in order to show the validity of the IS hydrodynamics. Employing the parton cascade we also investigate the formation of Mach shocks induced by a high-energy gluon traversing viscous gluon matter. For $η/s = 0.08$ a Mach cone structure is observed, whereas the signal smears out for $η/s \geq 0.32$.

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preprint2010arXiv

Study of magnetic alloy cores for HIRFL-CSRm compressor cavity

For selecting the properly magnetic alloy (MA) material to load the RF compression cavity, the measurement of the MA cores which is produced by Liyuan Company has been carried out at IMP. We measured 4 kinds of MA core materials, type V1, V2, A1 and A2. And we mainly focus on the permeability, quality factor (Q value) and shunt impedance of the MA core. The MA cores which have higher permeability, lower Q value and higher shunt impedance will be selected to load RF compression cavity. According to the results of measurement, the type V1, V2 and A2 material will be chosen as candidate to load RF cavity.

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preprint2010arXiv

Third-order dissipative hydrodynamics from the entropy principle

We review the entropy based derivation of third-order hydrodynamic equations and compare their solutions in one-dimensional boost-invariant geometry with calculations by the partonic cascade BAMPS. We demonstrate that Grad's approximation, which underlies the derivation of both Israel-Stewart and third-order equations, describes the transverse spectra from BAMPS with high accuracy. At the same time solutions of third-order equations are much closer to BAMPS results than solutions of Israel-Stewart equations. Introducing a resummation scheme for all higher-oder corrections to one-dimensional hydrodynamic equation we demonstrate the importance of higher-order terms if the Knudsen number is large.

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preprint2009arXiv

Shear viscosity and out of equilibrium dynamics

Using Grad's method, we calculate the entropy production and derive a formula for the second-order shear viscosity coefficient in a one-dimensionally expanding particle system, which can also be considered out of chemical equilibrium. For a one-dimensional expansion of gluon matter with Bjorken boost invariance, the shear tensor and the shear viscosity to entropy density ratio $η/s$ are numerically calculated by an iterative and self-consistent prescription within the second-order Israel-Stewart hydrodynamics and by a microscopic parton cascade transport theory. Compared with $η/s$ obtained using the Navier-Stokes approximation, the present result is about 20% larger at a QCD coupling $α_s \sim 0.3$(with $η/s\approx 0.18$) and is a factor of 2-3 larger at a small coupling $α_s \sim 0.01$. We demonstrate an agreement between the viscous hydrodynamic calculations and the microscopic transport results on $η/s$, except when employing a small $α_s$. On the other hand, we demonstrate that for such small $α_s$, the gluon system is far from kinetic and chemical equilibrium, which indicates the break down of second-order hydrodynamics because of the strong noneqilibrium evolution. In addition, for large $α_s$ ($0.3-0.6$), the Israel-Stewart hydrodynamics formally breaks down at large momentum $p_T\gtrsim 3$ GeV but is still a reasonably good approximation.

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preprint2008arXiv

QCD Matter Thermalization at RHIC and LHC

Employing the perturbative QCD inspired parton cascade, we investigate kinetic and chemical equilibration of the partonic matter created in central heavy ion collisions at RHIC and LHC energies. Two types of initial conditions are chosen. One is generated by the model of wounded nucleons using the PYTHIA event generator and Glauber geometry. Another is considered as a color glass condensate. We show that kinetic equilibration is almost independent on the chosen initial conditions, whereas there is a sensitive dependence for chemical equilibration. The time scale of thermalization lies between 1 and 1.5 fm/c. The final parton transverse energy obtained from BAMPS calculations is compared with the RHIC data and is estimated for the LHC energy.

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preprint2008arXiv

Review of the "Bottom-Up" scenario

Thermalization of a longitudinally expanding color glass condensate with Bjorken boost invariant geometry is investigated within parton cascade BAMPS. Our main focus lies on the detailed comparison of thermalization, observed in BAMPS with that suggested in the Bottom-Up scenario. We demonstrate that the tremendous production of soft gluons via $gg \to ggg$, which is shown in the Bottom-Up picture as the dominant process during the early preequilibration, will not occur in heavy ion collisions at RHIC and LHC energies, because the back reaction $ggg\to gg$ hinders the absolute particle multiplication. Moreover, contrary to the Bottom-Up scenario, soft and hard gluons thermalize at the same time. The time scale of thermal equilibration in BAMPS calculations is of order $\as^{-2} (\ln \as)^{-2} Q_s^{-1}$. After this time the gluon system exhibits nearly hydrodynamic behavior. The shear viscosity to entropy density ratio has a weak dependence on $Q_s$ and lies close to the lower bound of the AdS/CFT conjecture.

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